在这种背景下，数据挖掘技术应运而生。大数据帮助人们实现了将一
切运行的东西转换成数据并加以存储的愿望，数据挖掘技术则能够从
巨量数据中筛选、提取有用信息并构建智能分析体系，得出有决策参
考价值的结论。尤其是，近年来算法优化和数据建模领域的多项突破，
促使数据挖掘技术在包括财务分析在内的各个学科、领域得到快速的
推广应用
财务分析产生于二十世纪初期，在近百年的发展过程中已从最初
的贷款信用评价发展演变成企业重要的财务活动和决策支撑。随着科
技和经济领域进行的一系列变革，企业搜集存储的数据越来越多，传
统财务分析方法的缺点逐渐暴露，尤其是片面性和滞后性已经无法满
足现代企业的决策需求，数据挖掘在财务分析中的应用就越来越紧
迫，并显得尤为必要。企业内部因素和外部环境都影响着企业的财务
状况和运营状况，如何将数据挖掘技术与财务分析方法进行有机结
合，搜集、存储数据并将这些数据进行筛选、分析，最终挖掘出有用、
有价值的商业信息，让企业决策者能更及时准确地获知这些信息，进
而做出顺应时势的财务、战略决策，提高企业的市场竞争能力，仍然
是一个值得继续深入研究的课题
本文研究的是如何在集团公司内部构建以数据挖掘作为主要技
术的财务分析平台。全文共分为五部分，第一部分是绪论，阐述了本II
文的研究背景、意义以及研究方法，并介绍了国内外学者此前对大数
据时代数据挖掘财务分析系统的研究进展。第二部分界定了大数据这
一时代背景的内涵以及数据挖掘技术在财务管理领域的应用机理。第
三部分阐述了大数据时代数据挖掘技术在财务分析中的应用原理与
实现路径。分别从传统财务分析中的问题、数据挖掘技术对财务分析
的拓展深化与财务分析平台构建的路径三个方面阐述了大数据时代
数据挖掘技术与财务分析相融合的理论、现实意义和可行性。第四部
分以 S 集团为典型案例，分析了集团传统财务分析面临的困境以及构
建数据挖掘财务分析平台的应用效果和评价，以及不足之处和改进建
议。最后，第五部分总结全文并对未来研究方向做出了展望
关键词：大数据，数据挖掘，财务分析，系统平台搭建
论文类型：案例分析III
THE APPLICATION OF DATA MINING TECHNOLOGY
IN FINANCIAL ANALYSIS OF BIG DATA AGE
- TAKING S COMPANY AS AN EXAMPLE
ABSTRACT
Big Data, also known as huge amounts of information, is described in the era of
information explosion, in order to collect, store, analyze and process different
structures and types of data at a lower cost and more efficient way and obtain
decisions Value related technology. In the context of large data, people get data more
easily and swiftly, but still face too much data, the useful information is too little
confusion, people are eager to find a tool to be able to quickly deal with a large
number of short time. The different types of data, and ultimately generate information
with decision-making reference value. In this context, data mining technology came
into being. Big Data helps people realize the desire to convert everything to data and
store it. Data mining technology can filter from huge amounts of data, extract useful
information and construct intelligent analysis system, and draw the conclusion of
decision-making reference value. With the continuous improvement of data modeling
and algorithm optimization, data mining technology is widely used in various fields
including financial analysis with its powerful function.
Financial analysis originated in the early twentieth century, in the course of nearly a
hundred years of development from the initial loan credit evaluation development
evolved into an important financial activities and decision support. With the series of
changes in the fields of science and technology and economy, the data collected by
enterprises are more and more. The shortcomings of traditional financial analysis
methods are gradually exposed, especially the one-sidedness and lagging performance
can not meet the decision-making needs of modern enterprises. Financial analysis is
becoming more and more urgent and necessary. The internal factors and the external
environment of the enterprise all affect the financial status and operation status of the
enterprise. How can the data mining technology and the financial analysis method be
combined to collect and store the data, filter and analyze the data, which is value of
business information, so that business decision-makers can more timely and accurate
access to these information, and then make the trend of financial, strategic
decision-making, improve the market competitiveness of enterprises, is still a worthy
of further study of the subject.
This paper is based on the data mining technology based on the financial analysisIV
platform for the study of the object, and the full text is divided into five parts. The
first part is the introduction, introduces the research background, significance,
methods and domestic and foreign scholars of previous research progress. The second
part is the concept of elaboration, focusing on the large data background, data mining
technology and its application in the management principle. The third part elaborates
the application principle and the realization path of data mining technology in
financial analysis. This paper expounds the theoretical and practical significance and
feasibility of the combination of data mining technology and financial analysis from
three aspects: the problems in traditional financial analysis, the deepening of financial
analysis and the path of financial analysis platform. The fourth part takes the S group
as a typical case, analyzes the dilemma faced by the group&39;s traditional financial
analysis and the application effect and evaluation of the data mining financial analysis
platform, as well as the shortcomings and suggestions for improvement. Finally, the
fifth part summarizes the whole paper and makes a prospect for the future research
direction.
KEY WORDS: Large Data; Data Mining; Financial Analysis; ERP construction
TYPE OF DISSERTATION / THESIS: Case StudyV
目 录
1 绪论 ..1
1.1 研究背景和意义 ..........1
1.1.1 研究背景...........1
1.1.2 研究意义...........2
1.2 国内外文献综述 ..........2
1.2.1 国外文献综述.......2
1.2.2 国内研究综述.......3
1.3 研究内容与方法 ..........5
1.3.1 研究内容...........5
1.3.2 研究方法...........6
2 大数据时代数据挖掘技术主要内容及其一般性应用 ...........7
2.1 大数据内涵与时代背景 ....7
2.2 数据挖掘技术的一般问题 ..8
2.2.1 数据挖掘的内涵.....8
2.2.2 数据挖掘技术主要内容...........8
2.2.3 大数据时代数据挖掘技术的意义..10
2.3 数据挖掘技术在管理中的应用原理 .....11
2.3.1 数据挖掘解决问题的主要方法....11
2.3.2 数据挖掘主要应用模型..........12
3 大数据时代数据挖掘技术在企业财务分析中的应用原理与路径 14
3.1 传统财务分析的主要方法与存在的问题：基于数据挖掘角度 .......14
3.1.1 传统财务分析的主要方法........14
3.1.2 传统财务分析面临的困境........15
3.2 数据挖掘技术拓展企业财务分析职能的可行性 .......15
3.2.1 大数据时代数据挖掘技术与财务分析职能的深化15
3.2.2 数据挖掘技术应用于财务分析的可行性分析....17
3.3 构建数据挖掘技术财务分析平台：具体应用路径与流程 ...........18
3.3.1 数据挖掘财务分析平台的构建原则18
3.3.2 数据挖掘财务分析平台功能......19
3.3.3 数据挖掘财务分析平台的工作流程23
3.3.4 数据挖掘财务分析平台的安全保障机制........24
4 案例：大数据挖掘技术在 S 集团财务分析中的应用 ..........26VI
4.1 S 集团背景介绍..........26
4.2 S 集团传统财务分析中存在的问题......26
4.3 大数据时代 S 集团对数据挖掘财务分析平台应用 .....28
4.3.1 S 集团数据挖掘财务分析平台具体构建情况 ....28
4.3.2 S 集团数据挖掘财务分析平台应用 29
4.3.3 S 集团数据挖掘财务分析平台应用效果评价 ....31
4.4 平台构建与运用中存在的问题 .........37
4.4.1 未能有效挖掘非
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